# LVM
This is the model from paper: Sequential modeling enables scalable learning for large vision models.
https://arxiv.org/abs/2312.00785
LVM is a vision pretraining model that converts various kinds of visual data into visual sentences and performs next-token prediction autoregressively. It is compatible with both GPU and TPU.
LVM is built on top of [OpenLLaMA](https://github.com/openlm-research/open_llama) (an autoregressive model) and [OpenMuse](https://github.com/huggingface/open-muse) (a VQGAN that converts images into visual tokens).
This was trained in collaboration with HuggingFace. Thanks [Victor Sanh](https://huggingface.co/VictorSanh) for the support in this project.
## Key Differences from the Original Paper Version
1. We are currently releasing the 7B model (previously 3B). Additional model size variants will be available soon.
2. Deep filtering (including quality filters, deduplication, and known CSAM content removal) has been applied to the LAION dataset, reducing…
